The objective of this study is to perform a multidimensional technology assessment of percutaneous transluminal coronary angioplasty (PTCA), a recently introduced method of treating patients with coronary artery disease (CAD). Patients with chronic (more than 6 weeks) stable angina who are found at cardiac catheterization to have a greater than or equal to 75% stenosis of one or more coronary arteries will be eligible for this study. All patients will be classified by their attending angiographer according to their anatomic suitability for PTCA and for coronary bypass surgery (CABG). In addition, PTCA patients will be classified according to the therapy they would have received had PTCA not been available. A detailed data base consisting of demographic, clinical, catheterization, functional status, employment status and health resource consumption data will be collected on each patient prospectively. Each patient will also be followed for at least two years to determine outcome in terms of their clinical, functional and employment status and health resource consumption. Analyses will be performed to compare health outcomes and health care costs for PTCA patients and patients with equivalent severity of illness treated either medically or with CABG. Health outcomes to be examined include freedom from cardiac events (death, nonfatal myocardial infarction), functional capacity (measured by a new index developed and validated at Duke) and employment status. These data will be analyzed to determined the marginal costs and marginal benefits of PTCA as compared with medical therapy and coronary bypass surgery. Patient characteristics associated with high and low cost-effectiveness of PTCA will be identified to assist medical decision-making concerning individual patients. These data will also be analyzed to assess the overall impact of PTCA on health costs and outcomes under current patterns of utilization, as well as under alternative utilization patterns of interest to policy makers. Thus, results of this study should provide clinicians with methods for predicting the most cost- effective therapeutic choice for an individual CAD patient and provide health care policy makers with valid, sensitive tools for making resource allocation decisions.